Object-Detection-Using-yolov4-tiny

To understand this code, check this video:
1-- https://youtu.be/XaYRY4EM6is

2-- https://youtu.be/Bf2lrrdkpgs

Open convert_darknet_to_tensorflow_model. And do the below mentioned changes

1- Copy and paste your customdetector.weights file into the 'data' folder

2- Copy and paste your customdetector.names into the 'data/classes/' folder.

3- The only change within the code you need to make in order for your custom model to work is on line 14 of 'core/config.py' file. Update the code to point at your customdetector.names file

Open save_model.py file and replace the weights with your custom weight file

Commands to run

yolov4-tiny (converting darknet model into TensorFlow model)

python save_model.py --output ./checkpoints/yolov4-tiny-416 --input_size 416 --model yolov4 --framework tflite --tiny

convert yolov4-tiny tensorflow model into tflite

python convert_tflite.py --weights ./checkpoints/yolov4-tiny-416 --output ./checkpoints/yolov4-tiny-416.tflite

yolov4 quantize float16

python convert_tflite.py --weights ./checkpoints/ yolov4-tiny-416 --output ./checkpoints/yolov4-416-fp16.tflite --quantize_mode float16

Perform Detections

python detect.py --weights ./checkpoints/yolov4-tiny-416.tflite --size 416 --model yolov4 –images testimg.jfif --output ./output/outputtflite.jpg --framework tflite

Android App for Object Detection

Download that code from this link: https://github.com/tensorflow/examples/tree/master/lite/examples/object_detection/android